RT Journal Article
SR Electronic
T1 P282 Comparitive use of nhanes III, ECCS and GLI prediction equations in determining spirometric indices and suitability for anti-fibrotic therapy in patients with idiopathic pulmonary fibrosis
JF Thorax
JO Thorax
FD BMJ Publishing Group Ltd and British Thoracic Society
SP A241
OP A242
DO 10.1136/thoraxjnl-2016-209333.425
VO 71
IS Suppl 3
A1 Cliff, I
A1 Ali, A
A1 Spiteri, M
A1 Stone, H
YR 2016
UL http://thorax.bmj.com/content/71/Suppl_3/A241.2.abstract
AB Introduction Prediction equations are used to assess disease severity and prognosis in respiratory disease; globally most laboratories utilise ECCS or NHANES III equations. The Global Lung Initiative (GLI) produced reference ranges for spirometry that are multi-ethnic and applicable for patients upto the age of 95. The choice of which equation to use becomes crucial in idiopathic pulmonary fibrosis [IPF] patients, in whom prescription of currently available anti-fibrotic agents, Nintedanib and Pirfenidone is dependent on a forced vital capacity [FVC] between 50 and 80% of predicted in England and Wales (Scotland only restriction is FVC above 80% predicted).Methods Spirometric data recorded on 132 IPF patients were extracted from our BTS ILD Registry database. Values for FVC% predicted were calculated using the ECCS, NHANES III and GLI equations and compared to determine patient eligibility for anti-fibrotic treatment in line with published NICE Guidance.Results Data on 132 consecutive patients is presented in Table 1. This demonstrates the FVC% predicted when the 3 separate equations are used. At our centre, where ECCS is routinely used to calculate FVC% predicted, 62 patients (47%) of patients had an FVC above the upper limit of the treatment threshold of 80%. Of this group, 8 had evidence of more than 25% emphysematous change on their HRCT scans.View this table:Abstract P282 Table 1 Demographic data of the analysed cohort 132 patients with IPF, showing the proportional variation across the 3 prediction equations for determining eligibility for anti-fibrotic treatments using NICE cut-off ranges. Data are presented as mean values with standard deviations in parenthesesConclusions Using ECCS, 50% of patients met the NICE criteria for anti-fibrotic treatment. When NHANES III and GLI are used, patient eligibility for treatment increases to 61% and 59% respectively. Interestingly both the NHANES and GLI equations decrease the % predicted, and those patients that are just above the 80% cut off when ECCS is used become eligible for treatment just by using alternative prediction equations. The NICE Guidance does not specify which equation to use when assessing patients; in our patient cohort, the NHANES III or GLI would allow more patients to meet NICE eligibility for treatment. These data question, the use of predictive FVC cut-offs in prescribing anti-fibrotic treatments in a progressive lung disease without providing a national reference standard, especially when the particular prediction equation used could significantly impact on patients’ eligibility for treatment.